Demand coordination network control node

ABSTRACT

An apparatus for controlling peak demand of a system of energy consuming devices, including a first control node coupled to a second control node via a demand coordination network. The first control node has a node processor and a global schedule module. The node processor is coupled to a first energy consuming device, and operates the first energy consuming device within an acceptable operating margin to maintain a first local environment by cycling on and off. The global schedule module is coupled to the first node processor, and coordinates run times for the first energy consuming device and a second energy consuming device, where the coordination is based on a replica copy of a global run time schedule disposed within the first and second control nodes, an adjusted first descriptor set characterizing the first local environment, and an adjusted second descriptor set characterizing a second local environment.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of the following U.S. PatentApplication, which is herein incorporated by reference for all intentsand purposes.

SERIAL FILING NUMBER DATE TITLE 13,025,142 Feb. 10, 2011 APPARATUS ANDMETHOD (ENER.0101) FOR DEMAND COORDINATION NETWORK

Application Ser. No. 13/025,142 claims the benefit of the following U.S.Provisional Application, which is herein incorporated by reference forall intents and purposes.

SERIAL FILING NUMBER DATE TITLE 61,303,160 Feb. 10, 2010 APPARATUS ANDMETHOD FOR (SF.0101) DISRUPTION TOLERANT DEMAND COORDINATION NETWORK

This application is related to the following co-pending U.S. PatentApplications, each of which has a common assignee and common inventors.

SERIAL FILING NUMBER DATE TITLE 13,032,622 Feb. 22, 2011 APPARATUS ANDMETHOD (ENER.0103) FOR NETWORK-BASED GRID MANAGEMENT 13,601,622 Aug. 31,2012 NOC-ORIENTED CONTROL (ENER.0105) OF A DEMAND COORDINATION NETWORK13,617,782 Sep. 14, 2012 APPARATUS AND METHOD (ENER.0106) FOR RECEIVINGAND TRANSPORTING REAL TIME ENERGY DATA ( ENER.0101-C2) Apr. 17, 2013APPARATUS AND METHOD FOR CONTROLLING PEAK ENERGY DEMAND ( ENER.0101-C3)Apr. 17, 2013 CONFIGURABLE DEMAND MANAGEMENT SYSTEM

BACKGROUND OF THE INVENTION

1. Field of the Invention

This invention relates in general to the field of resource management,and more particularly to an apparatus and method for coordinating theuse of certain resources such that a peak demand of those resources isoptimized.

2. Description of the Related Art

The problem with resources such as electrical power, water, fossilfuels, and their derivatives (e.g., natural gas) is that the generationand consumption of a resource both vary with respect to time. Further,the delivery and transport infrastructure limits instantaneous matchingof generation and consumption. They are limited in supply and the demandfor this limited supply is constantly fluctuating. As anyone who hasparticipated in a rolling blackout will concur, the times are more andmore frequent when resource consumers are forced to face the realitiesof limited resource supply.

Most notably, the electrical power generation and distribution communityhas begun to take proactive measures to protect limited instantaneoussupplies of electrical power by imposing a demand charge on consumers inaddition to their monthly usage charge. Heretofore, consumers merelypaid for the total amount of power that they consumed over a billingperiod. Today most energy suppliers are not only charging customers forthe total amount of electricity they have consumed over the billingperiod, but they are additionally charging them for their peak demand,that is the greatest amount of energy that they use during a measuredperiod, typically on the order of minutes.

For example, consider a factory owner whose building includes 20 airconditioners, each consuming 10 KW when turned on. If they are all on atthe same time, then the peak demand for that period is 200 KW. Not onlydoes the energy supplier have to provide for instantaneous generation ofthis power in conjunction with loads exhibited by its other consumers,but the distribution network that supplies this peak power must be sizedsuch that it delivers 200 KW.

So it is acceptable today that high peak demand consumers are requiredto pay a surcharge to offset the costs of peak energy generation anddistribution. And the notion of peak demand charges, while presentlybeing levied only to commercial electricity consumers and to selectedresidential consumers, is applicable to all residential consumers andconsumers of other limited generation and distribution resources aswell. Water and natural gas are prime examples of resources that willsomeday exhibit demand charges.

But consider in the facility example above that it is not time orcomfort critical to run every air conditioning unit in the building atonce. Run times can be staggered, perhaps, to mitigate peak demand. Andthis technique is what is presently employed in the industry to lowerpeak demand. There are very simple ways to stagger run times, and thereare very complicated mechanisms that are employed to lower peak demand,but they all utilize variations of what is known in the art as deferral.

Stated simply, deferral means that some devices have to wait to runwhile other, perhaps higher priority, devices are allowed to run.Another form of deferral is to reduce the duty cycle (i.e., thepercentage of the a device cycle that a device is on) of one or moredevices in order to share the reduction in peak demand desired. Whatthis means in the air conditioning example above is that some folks aregoing to be very uncomfortable while waiting for their turn to run, orthat everyone in the facility is going to be mildly uncomfortable. Andas one skilled in the art will appreciate, there is a zone of comfortbeyond which productivity falls.

Virtually every system of resource consuming devices exhibits a marginof acceptable operation (“comfort zone” in the air conditioning exampleabove) around which operation of the device in terms of start time,duration, and duty cycle can be deferred. But the present inventors haveobserved that present day techniques for controlling peak demand allinvolve delaying (“deferring”) the start times and durations of devicesand decreasing the duty cycles, thus in many instances causing localenvironments to operate outside of their acceptable operational margins.It is either too hot, too cold, not enough water, the motors are notrunning long enough to get the job done, and etc.

Accordingly, what is needed is an apparatus and method for managing peakdemand of a resource that considers acceptable operational margins indetermining when and how long individual devices in a system will run.

What is also needed is a technique for scheduling run times for devicesin a controlled system that is capable of advancing the start times anddurations of those devices, and that is capable of increasing the dutycycles associated therewith in order to reduce demand while concurrentlymaintaining operation within acceptable operational margins.

What is additionally needed is a mechanism for modeling and coordinatingthe operation of a plurality of devices in order to reduce peak demandof a resource, where both advancement and deferral are employedeffectively to reduce demand and retain acceptable operationalperformance.

What is moreover needed is an demand coordination apparatus and methodthat employs adaptive modeling of local environments and anticipatoryscheduling of run times in order to reduce peak demand while maintainingacceptable operation.

Furthermore, what is needed is a demand coordination mechanism that willperform reliably and deterministically in the presence of periodicnetwork disruptions.

SUMMARY OF THE INVENTION

The present invention, among other applications, is directed to solvingthe above-noted problems and addresses other problems, disadvantages,and limitations of the prior art. The present invention provides asuperior technique for managing and controlling the demand level of agiven resource as that resource is consumed by a plurality of consumingdevices. In one embodiment, an apparatus for controlling peak demand ofa system of energy consuming devices. The apparatus includes a firstcontrol node that is coupled to a second control node via a demandcoordination network. The first control node has a node processor and aglobal schedule module. The node processor is coupled to a first energyconsuming device, and is configured to operate the first energyconsuming device within an acceptable operating margin to maintain afirst local environment by cycling on and off. The global schedulemodule is coupled to the first node processor, and is configured tocoordinate run times for the first energy consuming device and a secondenergy consuming device, where the coordination is based on a replicacopy of a global run time schedule disposed within the first and secondcontrol nodes, an adjusted first descriptor set characterizing the firstlocal environment, and an adjusted second descriptor set characterizinga second local environment.

One aspect of the present invention contemplates an apparatus forcontrolling peak demand of a system of energy consuming devices. Theapparatus includes a first control node that is coupled to a secondcontrol node via a demand coordination network. The first control nodehas a node processor, a global schedule module, and a local schedulemodule. The node processor is coupled to a first energy consumingdevice, and is configured to operate the first energy consuming devicewithin an acceptable operating margin to maintain a first localenvironment. The global schedule module is coupled to the first nodeprocessor, and is configured to coordinate run times for the firstenergy consuming device and a second energy consuming device, where thecoordination is based on a replica copy of a global run time scheduledisposed within the first and second control nodes, an adjusted firstdescriptor set characterizing the first local environment, and anadjusted second descriptor set characterizing a second localenvironment. The local schedule module is coupled to the node processorand the global schedule module, and is configured to direct the firstenergy consuming device to cycle on and off at appropriate times as afunction of a device actuation schedule provided by the global schedulemodule.

Another aspect of the present invention comprehends a method forcontrolling peak demand of a system of energy consuming devices. Themethod includes coupling a first control node and a second control nodetogether via a demand coordination network; via the first control node,operating a first energy consuming device within an acceptable operatingmargin to maintain a first local environment by cycling on and off; andcoordinating run times for the first energy consuming device and asecond energy consuming device, where the coordination is based on areplica copy of a global run time schedule disposed within the first andsecond control nodes respectively coupled to the first and second energyconsuming devices, an adjusted first descriptor set characterizing thefirst local environment, and an adjusted second descriptor setcharacterizing a second local environment.

BRIEF DESCRIPTION OF THE DRAWINGS

These and other objects, features, and advantages of the presentinvention will become better understood with regard to the followingdescription, and accompanying drawings where:

FIG. 1 is a block diagram illustrating a demand coordination systemaccording to the present invention;

FIG. 2 is a block diagram depicting a control node according to thepresent invention;

FIG. 3 is a block diagram featuring a local model module according tothe present invention, such as might be disposed within the control nodeof FIG. 2;

FIG. 4 is a timing diagram showing an exemplary local model estimationperformed by the local model module of FIG. 3;

FIG. 5 is a block diagram illustrating a global model module accordingto the present invention, such as might be disposed within the controlnode of FIG. 2;

FIG. 6 is a block diagram detailing a global schedule module accordingto the present invention, such as might be disposed within the controlnode of FIG. 2; and

FIG. 7 is a block diagram showing a local schedule module according tothe present invention, such as might be disposed within the control nodeof FIG. 2.

DETAILED DESCRIPTION

The following description is presented to enable one of ordinary skillin the art to make and use the present invention as provided within thecontext of a particular application and its requirements. Variousmodifications to the preferred embodiment will, however, be apparent toone skilled in the art, and the general principles defined herein may beapplied to other embodiments. Therefore, the present invention is notintended to be limited to the particular embodiments shown and describedherein, but is to be accorded the widest scope consistent with theprinciples and novel features herein disclosed.

In view of the above background discussion on resource and energy demandand associated techniques employed within systems to control peakdemand, a discussion of the present invention will now be presented withreference to FIGS. 1-7. The present invention provides for more flexibleand optimal management and control of resource consumption, such aselectrical energy, by enabling use of particular resources to becoordinated among resource consuming devices. In stark contrast to priorart mechanisms, the present invention employs scheduling techniques thatallow for advancement, or preemptive cycling of devices, as well asdeferral.

Referring to FIG. 1, a block diagram is presented illustrating a demandcoordination system 100 according to the present invention. The system100 includes a plurality of system devices 101, each of which is managedand controlled by the system 100 for purposes of consumption control inorder to manage peak resource demand. In one embodiment, the systemdevices 101 comprise air-conditioning units that are disposed within abuilding or other facility and the resource that is managed compriseselectrical power. In another embodiment, the system devices 101 compriseheating units that are disposed within a building or other facility andthe resource that is managed comprises natural gas. The presentinventors specifically note that the system 100 contemplated herein isintended to be preferably employed to control any type of resourceconsuming device 101 such as the units noted above, and also including,but not limited to, water pumps, heat exchangers, motors, generators,light fixtures, electrical outlets, sump pumps, furnaces, or any otherdevice that is capable of being duty-cycle actuated in order to reducepeak demand of a resource, but which is also capable, in one embodiment,of maintaining a desired level of performance (“comfort level”) byadvancing or deferring actuation times and increasing or decreasing dutycycles in coordination with other substantially similar devices 101. Thepresent inventors also note that the present invention comprehends anyform of consumable resource including, but not limited to, electricalpower, natural gas, fossil fuels, water, and nuclear power. As notedabove, present day mechanisms are in place by energy suppliers to levypeak demand charges for the consumption of electrical power by aconsumer and, going forward, examples are discussed in terms relative tothe supply, consumption, and demand coordination of electrical power forpurposes only of teaching the present invention in well-known subjectcontexts, but it noted that any of the examples discussed herein may bealso embodied to employ alternative devices 101 and resources discussedabove for the coordination of peak demand of those resources within asystem 100. It is also noted that the term “facility” is not to berestricted to construe a brick and mortar structure, but may alsocomprehend any form of interrelated system 100 of devices 101 whoseperformance can be modeled and whose actuations can be scheduled andcontrolled in order to coordinate demand of a particular resource.

Having noted the above, each of the devices 101 includes a devicecontrol 102 that operates to turn the device 101 on, thus consuming aresource, and off, thus not consuming the resource. When the device 101is off, none of the resource is consumed, and thus a device that is offdoes not contribute to overall cumulative peak resource demand. Thedevice control 102 does not have to be disposed within the device 101,nor does the device control 102 have to be collocated with the device101.

A control node 103 according to the present invention is coupled to eachof the device controls 102 via a device sense bus DSB 111 that isemployed by the control node 103 to turn the device 101 on and off, tosense when the device 101 is turned on and off, and to furthertransparently enable the device 101 to operate independent of the demandcoordination system 100 in a fail safe mode while at the same timesensing when the device 101 is turned on and turned off in the fail safemode. Each of the control nodes 103 maintain control of their respectivedevice 101 and in addition maintain a replicated copy of a global modelof a system environment along with a global schedule for actuation ofall of the devices 101 in the system 100. Updates to the global modeland schedule, along with various sensor, monitor, gateway,configuration, and status messages are broadcast over a demandcoordination network (DCN) 110, which interconnects all of the controlnodes 103, and couples these control nodes to optional global sensornodes 106, optional monitor nodes 109, and an optional gateway node 120.In one embodiment, the DCN 110 comprises an IEEE 802.15.4 packetizedwireless data network as is well understood by those skilled in the art.Alternatively, the DCN 110 is embodied as an IEEE 802.11 packetizedwireless or wired network. In another embodiment, the DCN 110 comprisesa power line modulated network comporting with HOMEPLUG® protocolstandards. Other packetized network configurations are additionallycontemplated. The present inventors note, however, that the presentinvention is distinguished from conventional “state machine” techniquesfor resource demand management and control in that only model updatesand schedule updates are broadcast over the DCN 110, thus providing astrong advantage according to the present invention in light of networkdisruption. For the 802.15.4 embodiment, replicated model and schedulecopies on each control node 103 along with model and schedule updatebroadcasts according to the present invention are very advantageous inthe presence of noise and multipath scenarios commonly experienced bywireless packetized networks. That is, a duplicate model update messagethat may be received by one or more nodes 103 does not serve to perturbor otherwise alter effective operation of the system 100.

Zero or more local sensors 104 are coupled to each of the control nodes103 via a local sensor bus 112, and configuration of each of the localsensors 104 may be different for each one of the devices 101. Examplesof local sensors 104 include temperature sensors, flow sensors, lightsensors, and other sensor types that may be employed by the control node103 to determine and model an environment that is local to a particularsystem device 101. For instance, a temperature sensor 104 may beemployed by a control node 103 to sense the temperature local to aparticular device 101 disposed as an air-conditioning unit. Another unitmay employ local sensors 104 comprising both a temperature and humiditysensor local to a device 101 disposed as an air-conditioning unit. Otherexamples abound. Other embodiments contemplate collocation of localsensors 104 and device control 102 for a device 101, such as thewell-known thermostat.

The system 100 also optionally includes one or more global sensors 105,each of which is coupled to one or more sensor nodes 106 according tothe present invention. The sensors 105 may comprise, but are not limitedto, occupancy sensors (i.e., movement sensors), solar radiation sensors,wind sensors, precipitation sensors, humidity sensors, temperaturesensors, power meters, and the like. The sensors 105 are such that theirdata is employed to globally affect all modeled environments andschedules. For example, the amount of solar radiation on the facilityhas an impact to each local environment associated with each of thesystem devices 101, and therefore must be taken into account whendeveloping a global model of the system environment. In one embodiment,the global model of the system environment is an aggregate of all localmodels associated with each of the devices, where each of the localmodels are adjusted based upon the data provided by the global sensors105.

Each of the global sensors 105 is coupled to a respective sensor node106 according to the present invention via a global sensor bus (GSB)113, and each of the sensor nodes 106 are coupled to the DCN 110.Operationally, the sensor nodes 106 are configured to sample theirrespective global sensor 105 and broadcast changes to the sensor dataover the DCN 110 to the control nodes 110 and optionally to the gatewaynode 120.

The system 100 also optionally includes one or more non-system devices107, each having associated device control 108 that is coupled to arespective monitor node 109 via a non-system bus (NSB) 114. Each of themonitor nodes 109 is coupled to the DCN 110. Operationally, each monitornode 109 monitors the state of its respective non-system device 107 viaits device control 108 to determine whether the non-system device 107 isconsuming the managed resource (i.e., turned on) or not (i.e., turnedoff). Changes to the status of each non-system device 107 is broadcastby its respective monitor node 109 over the DCN 110 to the control nodes103 and optionally to the gateway node 120. The non-system devices 107may comprise any type of device that consumes the resource beingmanaged, but which is not controlled by the system 100. One example ofsuch a non-system device 107 is an elevator in a building. The elevatorconsumes electrical power, but may not be controlled by the system 100in order to reduce peak demand. Thus, in one embodiment, consumption ofthe resource by these non-system devices 107 is employed as a factorduring scheduling of the system devices 101 in order to manage andcontrol peak demand of the resource.

Optionally, the gateway node 120 is coupled by any known means to anetwork operations center (NOC) 121. In operation, configuration datafor the system 100 may be provided by the NOC 121 and communicated tothe gateway node 120. Alternatively, configuration data may be providedvia the gateway node 120 itself. Typically, the gateway node 120 iscollocated with the system 100 whereas the NOC 121 is not collocated andthe NOC 121 may be employed to provide configuration data to a pluralityof gateway nodes 120 corresponding to a plurality of systems 100. Theconfiguration data may comprise, but is not limited to, device controldata such as number of simultaneous devices in operation, deviceoperational priority relative to other devices, percentage of peak loadto employ, peak demand profiles related to time of day, and the like.

Thus, as will be described in more detail below, each of the controlnodes 103 develops a local environment model that is determined fromcorresponding local sensors 104. Each local environment model, aschanges to the local environment model occur, is broadcast over the DCN110 to all other control nodes 103. Each of the control nodes 103 thusmaintains a global environmental model of the system 100 which, in oneembodiment, comprises an aggregation of all of the local environmentalmodels. Each of the global models is modified to incorporate the effectof data provided by the global sensors 105. Thus, each identical globalmodel comprises a plurality of local environmental models, each of whichhas been modified due to the effect of data provided by the globalsensors 105. It is important to note that the term “environmental” isintended to connote a modeling environment as opposed to a physicalenvironment.

Each control node 103, as will be described below, additionallycomprises a global schedule which, like the global model, is anaggregate of a plurality of local run time schedules, each associatedwith a corresponding device 101. The global schedule utilizes the globalmodel data in conjunction with configuration data and data provided bythe monitor nodes 109, to develop the plurality of local run timeschedules, where relative start times, duration times, and duty cycletimes are established such that comfort margins associated with each ofthe local environments are maintained, in one embodiment, viamaintaining, advancing (i.e., running early), or deferring (i.e.,delaying) their respective start times and durations, and viamaintaining, advancing, or deferring their respective duty cycles.

Turning now to FIG. 2, a block diagram is presented depicting a controlnode 200 according to the present invention. The control node 200includes a node processor 201 that is coupled to one or more localsensors (not shown) via a local sensor bus (LSB) 202, a device control(not shown) via a device sense bus (DSB) 203, and to a demandcoordination network (DCN) 204 as has been described above withreference to FIG. 1.

The control node 200 also includes a local model module 204 that iscoupled to the node processor 201 via a synchronization bus (SYNC) 209,a sensor data bus (SENSEDATA) 215, and a device data bus (DEVDATA) 216.The control node 200 also has a global model module 206 that is coupledto the node processor 201 via SYNC 209 and via an inter-node messagingbus (INM) 211. The global model module 206 is coupled to the local modelmodule 205 via a local model environment bus (LME) 212. The control node200 further includes a global schedule module 207 that is coupled to thenode processor 201 via SYNC 209 and INM 211, and that is coupled to theglobal model module 206 via a global relative run environment bus (GRRE)213. The control node finally includes a local schedule module 208 thatis coupled to the node processor 201 via SYNC 209 and a run control bus(RUN CTRL) 210. The local schedule module 208 is also coupled to theglobal schedule module 207 via a local relative run environment bus(LRRE) 214. LRRE 214 is also coupled to the global model module 206. Inaddition, a run time feedback bus (RTFB) 217 couples the local schedulemodule 208 to the local model module 205.

The node processor 201, local model module 205, global model module 206,global schedule model 207, and local schedule model 208 according to thepresent invention are configured to perform the operations and functionsas will be described in further detail below. The node processor 201local model module 205, global model module 206, global schedule model207, and local schedule model 208 each comprises logic, circuits,devices, or microcode (i.e., micro instructions or native instructions),or a combination of logic, circuits, devices, or microcode, orequivalent elements that are employed to perform the operations andfunctions described below. The elements employed to perform theseoperations and functions may be shared with other circuits, microcode,etc., that are employed to perform other functions within the controlnode 200. According to the scope of the present application, microcodeis a term employed to refer to one or more micro instructions.

In operation, synchronization information is received by the nodeprocessor 201. In one embodiment, the synchronization information istime of day data that is broadcast over the DCN 204. In an alternativeembodiment, a synchronization data receiver (not shown) is disposedwithin the node processor 201 itself and the synchronization dataincludes, but is not limited to, atomic clock broadcasts, a receivableperiodic synchronization pulse such as an amplitude modulatedelectromagnetic pulse, and the like. The node processor 201 is furtherconfigured to determine and track relative time for purposes of taggingevents and the like based upon reception of the synchronization data.Preferably, time of day is employed, but such is not necessary foroperation of the system.

The node processor 201 provides periodic synchronization data via SYNC209 to each of the modules 205-208 to enable the modules 205-208 tocoordinate operation and to mark input and output data accordingly. Thenode processor 201 also periodically monitors data provided by the localsensors via LSB 202 and provides this data to the local model module 205via SENSEDATA 215. The node processor 201 also monitors the DSB 203 todetermine when an associated device (not shown) is turned on or turnedoff. Device status is provided to the local model module 205 viaDEVDATA. The node processor 201 also controls the associated device viathe DSB 203 as is directed via commands over bus RUN CTRL 210. The nodeprocessor further transmits and receives network messages over the DCN204. Received message data is provided to the global model module 206 orthe global schedule model 207 as appropriate over bus INM 211. Likewise,both the global model module 206 and the global schedule model 207 mayinitiate DCN messages via commands over bus INM 211. These DCN messagesprimarily include, but are not limited to, broadcasts of global modelupdates and global schedule updates. System configuration message dataas described above is distributed via INM 211 to the global schedulemodule 207.

Periodically, in coordination with data provide via SYNC 209, the localmodel module employs sensor data provided via SENSEDATA 215 inconjunction with device actuation data provided via DEVDATA 216 todevelop, refine, and update a local environmental model which comprises,in one embodiment, a set of descriptors that describe a relative timedependent flow of the local environment as a function of when theassociated device is on or off. For example, if the device is an airconditioning unit and the local sensors comprise a temperature sensor,then the local model module 205 develops, refines, and updates a set ofdescriptors that describe a local temperature environment as a relativetime function of the data provided via SYNC 209, and furthermore as afunction of when the device is scheduled to run and the parametersassociated with the scheduled run, which are received from the localschedule module 208 via RTFB 217. This set of descriptors is provided tothe global model module 206 via LME 212. However, it is noted that thesedescriptors are updated and provided to LME 212 only when one or more ofthe descriptors change to the extent that an error term within the localmodel module 205 is exceeded. In addition to the descriptors, dataprovided on LME 212 by the local model module includes an indication ofwhether the descriptors accurately reflect the actual local environment,that is, whether the modeled local environment is within an acceptableerror margin when compared to the actual local environment. When themodeled local environment exceeds the acceptable error margin whencompared to the actual local environment, then the local model module205 indicates that its local environment model is inaccurate over LME212, and the system may determine to allow the associated device to rununder its own control in a fail safe mode. For instance, if occupancy ofa given local area remains consistent, then a very accurate model of thelocal environment will be developed over a period of time, and updatesof the descriptors 212 will decrease in frequency, thus providingadvantages when the DCN 204 is disrupted. It is noted that the errorterm will decrease substantially in this case. However, consider astable local environment model that is continually perturbed by eventsthat cannot be accounted for in the model, such as impromptu gatheringsof many people. In such a case the error term will be exceeded, thuscausing the local model module 205 to indicate over LME 212 that itslocal environment model is inaccurate. In the case of a systemcomprising air conditioning units, it may be determined to allow theassociated unit to run in fail safe mode, that is, under control of itslocal thermostat. Yet, advantageously, because all devices continue touse their replicated copies of global models and global schedules, thedevices continue to operate satisfactorily in the presences ofdisruption and network failure for an extended period of time.Additionally, if model error over time is known, then all devices in thenetwork can utilize pre-configured coordination schedules, effectivelycontinuing coordination over an extended period of time, in excess ofthe models ability to stay within a known margin of error. Furthermore,it can be envisioned that devices without a DCN, utilizing someexternally sensible synchronization event, and with known modelenvironments, could perform coordination sans DCN.

The local model module 205, in addition to determining the above noteddescriptors, also maintains values reflecting accuracy of the localsensors, such as hysteresis of a local thermostat, and accounts for suchin determining the descriptors. Furthermore, the local model module 205maintains and communicates via LME 212 acceptable operation margin datato allow for advancement or deferral of start times and durations, andincrease or decrease of duty cycles. In an air conditioning or heatingenvironment, the acceptable operation margin data may comprise an upperand lower temperature limit that is outside of the hysteresis of thelocal temperature sensor, but that is still acceptable from a humanfactors perspective in that it is not noticeable to a typical person,thus not adversely impacting that person's productivity.

In one embodiment, the descriptors comprise one or more coefficients andan offset associated with a linear device on equation and one or morecoefficients and intercept associated with a linear device off equation.Other equation types are contemplated as well to include second orderequations, complex coefficients, or lookup tables in the absence ofequation-based models. What is significant is that the local modelmodule generates and maintains an acceptable description of its localenvironment that is relative to a synchronization event such that theglobal model module 206 can predict the local environment as seen by thelocal model module.

The global model module 206 receives the local descriptors via LME 212and stores this data, along with all other environments that arebroadcast over the DCN and received via the INM 211. In addition, theglobal model module adjusts its corresponding local environment entry totake into account sensor data from global sensors (e.g., occupancysensors, solar radiation sensors) which is received over the DCN 204 andprovided via the INM 211. An updated local entry in the global modelmodule 206 is thus broadcast over the DCN 204 to all other control nodesin the system and is additionally fed back to the local model module toenable the local model module to adjust its local model to account forthe presence of global sensor data.

The global model module 206 provides all global model entries to theglobal schedule module 207 via GRRE 213. The global schedule module 207employs these models to determine when and how long to actuate each ofthe devices in the system. In developing a global device schedule, theglobal schedule module utilizes the data provided via GRRE 213, that is,aggregate adjusted local models for the system, along with systemconfiguration data as described above which is resident at installationor which is provided via a broadcast over the DCN 204 (i.e., aNOC-initiated message over the gateway node). The global deviceactuation schedule a schedule of operation relative to thesynchronization event and is broadcast over the DCN 204 to all othercontrol nodes. In addition, the device actuation schedule associatedwith the specific control node 200 is provided over LRRE 214 to both thelocal schedule module 208 and the local model module, for this datadirects if and when the device associated with the specific control node200 will run. It is noted that the global schedule module 207 operatessubstantially to reduce peak demand of the system by advancing ordeferring device start times and increasing or decreasing device dutycycles in accordance with device priorities. The value by which a timeis advanced or deferred and the amount of increase or decrease to a dutycycle is determined by the global schedule module 207 such that higherpriority devices are not allowed to operate outside of their configuredoperational margin. In addition, priorities, in one embodiment, aredynamically assigned by the global schedule module 207 based upon theeffect of the device's timing when turned on. Other mechanisms arecontemplated as well for dynamically assigning device priority withinthe system.

The local schedule module 208 directs the associated device to turn onand turn off at the appropriate time via commands over RUN CTRL 210,which are processed by the node processor 201 and provided to the devicecontrol via DSB 203.

Now referring to FIG. 3, a block diagram is presented featuring a localmodel module 300 according to the present invention, such as might bedisposed within the control node 200 of FIG. 2. As is described abovewith reference to FIG. 2, the local model module 300 performs thefunction of developing, updating, and maintaining an acceptably accuratemodel of the local environment. Accordingly, the local model module 300includes a local data processor 301 that is coupled to busses SENSEDATA,DEVDATA, SYNC, and RTFB. Data associated with the local environment isstamped relative to the synchronization data provided via SYNC andentries are provided to a local data array 302 via a tagged entry busTAGGED ENTRY. The local model module 300 also includes a local modelestimator 303 that is coupled to the local data array 302 and whichreads the tagged entries and develops the descriptors for the localenvironment when the device is on an when the device is off, asdescribed above. The local model estimator 303 include an initiationprocessor 304 that is coupled to an LME interface 306 via bus ONLINE andan update processor 305 that is coupled to the LME interface 306 via busNEW. The LME interface 306 generates data for the LME bus.

In operation, the local data processor 301 monitors SENSEDATA, DEVDATA,and RTFB. If data on any of the busses changes, then the local dataprocessor 301 creates a tagged entry utilizing time relative to dataprovided via SYNC and places the new tagged entry into the local dataarray 302. Periodically, the local model estimator 303 examines theentries in the local data array 302 and develops the descriptorsdescribed above. The period at which this operation is performed is afunction of the type of devices in the system. In one embodiment,development of local environment model descriptors is performed atintervals ranging from 1 second to 10 minutes, although one skilled inthe art will appreciate that determination of a specific evaluationinterval time is a function of device type, number of devices, andsurrounding environment. The update processor 305 monitors successiveevaluations to determine if the value of one or more of the descriptorschanges as a result of the evaluation. If so, then the update processor305 provides the new set of descriptors to the LME interface 306 via busNEW.

The initialization processor 304 monitors the accuracy of the modeledlocal environment as compared to the real local environment. If theaccuracy exceeds and acceptable error margin, then the initializationprocessor 304 indicates such via bus ONLINE and the LME interface 306reports this event to the global model module (not shown) via bus LME.As a result, the local device may be directed to operate in fail safemode subject to constraints and configuration data considered by theglobal schedule module (not shown). Advantageously, the initializationprocessor 304 enables a control node according to the present inventionto be placed in service without any specific installation steps. Thatis, the control node is self-installing. In one embodiment, as the localmodel module learns of the local environment, the initializationprocessor 304 indicates that the error margin is exceeded and as aresult the local device will be operated in fail safe mode, that is, itwill not be demand controlled by the system. And when development of thelocal model falls within the error margin, the initialization processor304 will indicate such and the local device will be placed online andits start times and durations will be accordingly advanced or deferredand its duty cycle will be increased or decreased, in conjunction withother system devices to achieve the desired level of peak demandcontrol.

Turning to FIG. 4, a timing diagram 400 is presented showing anexemplary local model estimation performed by the local model module ofFIG. 3. The diagram 400 includes two sections: a parameter estimationsection 401 and a device state section 402. The parameter estimationsection 401 shows a setpoint for the device along with upper and lowerhysteresis values. In some devices, hysteresis is related to theaccuracy of the local sensor. In other devices, hysteresis is purposelybuilt in to preclude power cycling, throttling, oscillation, and thelike. In a cooling or heating unit, the hysteresis determines how oftenthe device will run and for how long. The parameter estimation section401 also shows an upper operational margin and a lower operationalmargin, outside of which the local device is not desired to operate. Theparameter estimation section 401 depicts an estimated device off line(UP) 403 that is the result of applying estimated descriptors over timefor when the device is turned off, and an estimated device on line (DN)404 that is the result of applying estimated descriptors over time forwhen the device is turned on. One area of demand control where thisexample is applicable is for a local air conditioning unit that iscontrolled by a local thermostat. Accordingly, the local data processor301 provides tagged entries to the local data array 302 as noted above.Device status (on or off) is provided either directly from DEVDATA busor indirectly from RTFB (if DEVDATA is incapable of determining on andoff state). The entries corresponding to each of the two states areevaluated and a set of descriptors (i.e., parameters) are developed thatdescribe the local environment. In one embodiment, a linear fitalgorithm is employed for the on time and off time of the device. Byusing device status 405, the local model estimator 303 can determinedescriptors for UP 403, DN 404, and the upper and lower hysteresislevels. Upper and lower margin levels are typically provided byconfiguration. In the air conditioning example, the parameter beingestimated is local temperature and thus the upper and lower marginswould vary perhaps two degrees above and below the hysteresis levels.Note that prior to time T1, the device is off and the parameter, asindicated by local sensor data, is increasing. At time T1 the deviceturns on, subsequently decreasing the parameter. At time T2, the deviceturns off and the parameter begins increasing in value. At time T3 thedevice turns on again and the parameter decreases. At time T4, thedevice turns off and the parameter increases.

By determining the descriptors and knowing the upper and lower margins,a global scheduler is enabled to determine how long it can advance(point TA) or delay (TD) a start time, for example. In addition, thedescriptors developed by the local model for the operational curves 403,404, as adjusted by the global model module, enable a global schedulerto advance or defer start and/or duration, or increase or decrease dutycycle of the device in a subsequent cycle in order to achieve thedesired peak demand control while maintaining operation of the devicewithin the upper and lower margin boundaries. Advantageously, the modelaccording to the present invention is configured to allow for estimationof the precise position in time of the device on the curves 403, 404,which enables, among other features, the ability of the system toperform dynamic hysteresis modification, or overriding intrinsichysteresis of a device. In addition, the initialization processor 304can monitor the actual environment from local sensor data and compare itto the curves 403, 404 to determine if and when to place the deviceonline for demand control. The descriptors that describe the UP segment403 and DN segment 404 are communicated to the global model module viabus LME.

Now referring to FIG. 5, a block diagram illustrating a global modelmodule 500 according to the present invention, such as might be disposedwithin the control node 200 of FIG. 2. As is noted in the discussionwith reference to FIG. 2, the global model module 500 performs twofunctions. First, the global model module 500 adjusts the descriptorsassociated with the local environment as provided over bus LME toaccount for global sensor data provided via messages broadcast forglobal sensor nodes over the demand control network. Secondly, theglobal model module stores replica copies of all other local environmentdescriptors in the system, as each of those local environmentdescriptors have been adjusted by their respective global model modules.

The global model module 500 includes a global data processor 501 thatreceives local descriptors and other data via bus LME from itscorresponding local model module. In addition, the global data processor501 interfaces to busses INM, SYNC, and LRRE to receive/transmit data asdescribed above. Local descriptors are stamped and entered into a globaldata array 502 via bus LME entry. The remaining adjusted localdescriptors from other devices are received via bus INM and are enteredinto the global data array 502 via bus GLB entry.

A global model estimator 503 is coupled to the global data array 502 andto the global data processor 501 via busses GLB SENSOR DATA, ACTUALLOCAL RUN DATA, and UPDATE MESSAGE DATA. Global sensor data that isreceived over INM is provided to the estimator 503 via GLB SENSOR DATA.Actual run time data for the corresponding local device that is receivedover bus LRRE is provided to the estimator 503 via ACTUAL LOCAL RUNDATA.

In operation, the global model estimator 503 retrieves its correspondinglocal environment descriptor entry from the global data array 502. Theglobal model estimator 503 includes an environment updater 504 thatmodifies the local descriptor retrieved from the array to incorporatethe effects of global sensor data provided over GLB SENSOR DATA. Forexample, the value of an external building temperature sensor is aparameter that would affect every local temperature descriptor set inthe system. The environment updater 504 modifies its local descriptorset to incorporate any required changes due to global sensor values. Inaddition, the environment updater 504 employs the actual run data of theassociated device to enable it to precisely determine at what point onthe estimated local environmental curve that it is at when modifying thelocal descriptors.

If the environment updater 504 modifies a local descriptor set, itscorresponding entry in the array 502 is updated and is provided to amessaging interface 506 and to a GRRE interface. The messaging interface506 configures update message data and provides this data via UPDATEMESSAGE DATA to the processor 501 for subsequent transmission over theDCN. The GRRE interface 505 provides the updated local environmentdescriptor set to bus GRRE. All operations are performed relative tosynchronization event data provided via SYNC.

Turning to FIG. 6, a block diagram is presented detailing a globalschedule module 600 according to the present invention, such as might bedisposed within the control node 200 of FIG. 2. As described above, theglobal schedule module 600 is responsible for determining a schedule ofoperation (turn on, duration, and duty cycle) for each of the devices inthe system. When the local environment descriptors are updated by acoupled global model module and are received over bus GRRE, then theglobal schedule module 600 operates to revise the global schedule ofdevice operation and to broadcast this updated schedule over the DCN.

The global schedule module 600 includes a global data processor 601 thatinterfaces to INM for reception/transmission of DCN related data, busGRRE for reception of updated local environment descriptors, and busSYNC for reception of synchronization event data. DCN data that isprovided to the global schedule module 600 includes broadcast globalschedules from other control nodes, and non-system device data andconfiguration data as described above. The global data processor 601provides updated global schedule data, received over the DCN from theother control nodes, to a global schedule array 602 via bus GLB ENTRY.The global processor 601 is coupled to a global scheduler 603 via busNON-SYSTEM/CONFIG DATA for transmittal of the non-system device data andconfiguration data. The global processor 601 is also coupled to theglobal scheduler 603 via bus GRRE data for transmittal of updated localenvironment descriptors provided via bus GRRE. And the global scheduler603 is coupled to the processor 601 via bus UPDATE MESSAGE DATA toprovide INM data resulting in DCN messages that broadcast an updatedglobal schedule generated by this module 600 to other control nodes inthe system.

The global scheduler 603 includes a demand manager 604 that is coupledto an LRRE interface 605 via bus LOC and to a messaging interface 606via bus UPDATE. When data is received over either the NON-SYTEM/CONFIGDATA bus or the GRRE data bus, the demand manager recalculates a globalrelative run schedule for all devices in the system. The schedule for anindividual device includes, but is not limited to, a relative starttime, a duration, and a duty cycle. The relative start time and/orduration may be advanced, maintained, or deferred in order to achieveconfigured constraints of the system in conjunction with the operationof non-system devices and the amount of resource that they consume. Inaddition, for similar purposes the duty cycle for each device in thesystem may be increased or decreased. Yet, as one skilled willappreciate, the system accounts for limits to devices duty cyclemodification to prevent unintended damage to a device. The result is anupdated global schedule, which is stored in the array 602, and which isbroadcast via update messages over the DCN provided via bus UPDATE. Inaddition, the relative run schedule for the corresponding local deviceis provided via bus LOC to the LRRE interface 605, and which is placedon bus LRRE for transmission to a corresponding local schedule module.

FIG. 7 is a block diagram showing a local schedule module 700 accordingto the present invention, such as might be disposed within the controlnode 200 of FIG. 2. The local schedule module 700 includes a localschedule processor 701 that is coupled to bus RUN CTRL, bus LRRE, busSYNC, and bus RTFB. The local schedule processor 701 includes areal-time converter 702 and a fail safe manager 703.

In operation, the local schedule processor 701 receives an updated localrun schedule for its associated device. The real-time converterestablishes an actual run time for the device based upon thesynchronization data provided via SYNC and the relative run time datareceived over LRRE. This real-time data is provided to a correspondinglocal model module via bus RTFB to enable the local model module toestablish device on/off times in the absence of the device's ability toprovide that data itself. Accordingly, the processor 701 directs thedevice to turn on and turn off via commands over RUN CTRL in comportwith the actual run time schedule. In the event that the LRRE includesan indication that the local model is not within an acceptable errorrange, as described above, the fail safe manager 703 directs the devicevia RUN CTRL to operate independently.

Although the present invention and its objects, features, and advantageshave been described in detail, other embodiments are encompassed by theinvention as well. For example, the present invention has been primarilydescribed herein as being useful for managing consumption side peakdemand. However, the scope of the present invention extends to a systemof devices (e.g., generators) on the supply side for controlling thesupply of a resource. Such is an extremely useful application that iscontemplated for supply of a resource by a resource supplier havingnumerous, but not simultaneously operable supply devices. One suchexample is a state-wide electrical supply grid.

In addition, the present invention comprehends geographicallydistributed systems as well to include a fleet of vehicles or any otherform of system whose local environments can be modeled and associateddevices controlled to reduce peak demand of a resource.

Moreover, the present invention contemplates devices that comprisevariable stages of consumption rather than the simple on/off stagesdiscussed above. In such configurations, a control node according to thepresent invention is configured to monitor, model, and control avariable stage consumption device.

Those skilled in the art should appreciate that they can readily use thedisclosed conception and specific embodiments as a basis for designingor modifying other structures for carrying out the same purposes of thepresent invention, and that various changes, substitutions andalterations can be made herein without departing from the scope of theinvention as defined by the appended claims.

What is claimed is:
 1. An apparatus for controlling peak demand of a system of energy consuming devices, the apparatus comprising: a first control node, coupled to a second control node via a demand coordination network, said first control node comprising: a node processor, coupled to a first energy consuming device, configured to operate the first energy consuming device within an acceptable operating margin to maintain a first local environment by cycling on and off; and a global schedule module, coupled to said first node processor, configured to coordinate run times for said first energy consuming device and a second energy consuming device, wherein the coordination is based on a replica copy of a global run time schedule disposed within said first and second control nodes, an adjusted first descriptor set characterizing said first local environment, and an adjusted second descriptor set characterizing a second local environment.
 2. The apparatus as recited in claim 1, wherein said global schedule module coordinates said run times to reduce the peak demand of an energy resource.
 3. The apparatus as recited in claim 1, wherein said global schedule module coordinates said run times by advancing a first start time.
 4. The apparatus as recited in claim 3, wherein said global schedule module coordinates said run times by deferring a second start time.
 5. The apparatus as recited in claim 4, wherein said global schedule module coordinates said run times by increasing a duty cycle.
 6. The apparatus as recited in claim 1, wherein said first control node further comprises: a local model module, coupled to said node processor and said global model module, configured to develop a third descriptor set characterizing a third local environment associated with said first energy consuming device.
 7. The apparatus as recited in claim 6, wherein said first control node further comprises: a global model module, coupled to said node processor, said local model module, and said global schedule module, configured to develop said adjusted first and second descriptor sets, wherein said adjusted first and second descriptor sets are based upon said third descriptor set, a fourth descriptor set characterizing a fourth local environment associated with said second energy consuming device, and global sensor data received over said demand coordination network.
 8. An apparatus for controlling peak demand of a system of energy consuming devices, the apparatus comprising: a first control node, coupled to a second control node via a demand coordination network, said first control node comprising: a node processor, coupled to a first energy consuming device, configured to operate the first energy consuming device within an acceptable operating margin to maintain a first local environment; a global schedule module, coupled to said first node processor, configured to coordinate run times for said first energy consuming device and a second energy consuming device, wherein the coordination is based on a replica copy of a global run time schedule disposed within said first and second control nodes, an adjusted first descriptor set characterizing said first local environment, and an adjusted second descriptor set characterizing a second local environment; and a local schedule module, coupled to said node processor and said global schedule module, configured to direct said first energy consuming device to cycle on and off at appropriate times as a function of a device actuation schedule provided by said global schedule module.
 9. The apparatus as recited in claim 8, wherein said global schedule module coordinates said run times to reduce the peak demand of an energy resource.
 10. The apparatus as recited in claim 8, wherein said global schedule module coordinates said run times by advancing a first start time.
 11. The apparatus as recited in claim 10, wherein said global schedule module coordinates said run times by deferring a second start time.
 12. The apparatus as recited in claim 11, wherein said global schedule module coordinates said run times by increasing a duty cycle.
 13. The apparatus as recited in claim 8, wherein said first control node further comprises: a local model module, coupled to said node processor and said global model module, configured to develop a third descriptor set characterizing a third local environment associated with said first energy consuming device.
 14. The apparatus as recited in claim 13, wherein said first control node further comprises: a global model module, coupled to said node processor, said local model module, and said global schedule module, configured to develop said adjusted first and second descriptor sets, wherein said adjusted first and second descriptor sets are based upon said third descriptor set, a fourth descriptor set characterizing a fourth local environment associated with said second energy consuming device, and global sensor data received over said demand coordination network.
 15. A method for controlling peak demand of a system of energy consuming devices, the method comprising: coupling a first control node and a second control node together via a demand coordination network; via the first control node, operating a first energy consuming device within an acceptable operating margin to maintain a first local environment by cycling on and off; and coordinating run times for the first energy consuming device and a second energy consuming device, wherein the coordination is based on a replica copy of a global run time schedule disposed within the first and second control nodes respectively coupled to the first and second energy consuming devices, an adjusted first descriptor set characterizing the first local environment, and an adjusted second descriptor set characterizing a second local environment.
 16. The method as recited in claim 15, wherein said coordinating is performed to reduce the peak demand of an energy resource.
 17. The method as recited in claim 15, wherein said coordinating comprises: advancing a first start time.
 18. The method as recited in claim 17, wherein said coordinating further comprises: deferring a second start time.
 19. The method as recited in claim 18, wherein said coordinating further comprises: increasing a duty cycle.
 20. The method as recited in claim 15, wherein the method further comprises: first developing a third descriptor set characterizing a third local environment associated with the first energy consuming device; and second developing the adjusted first and second descriptor sets, said second developing is based upon the third descriptor set, a fourth descriptor set characterizing a fourth local environment associated with the second energy consuming device, and global sensor data received over the demand coordination network. 